update
This commit is contained in:
narawat lamaiin
@@ -1,7 +1,7 @@
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module llmfunction
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export virtualWineUserChatbox, jsoncorrection, checkinventory,
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virtualWineUserRecommendbox, userChatbox, userRecommendbox, extractWineAttributes
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virtualWineUserRecommendbox, userChatbox, userRecommendbox
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using HTTP, JSON3, URIs, Random, PrettyPrinting, UUIDs
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using GeneralUtils, SQLLLM
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@@ -365,12 +365,12 @@ julia> result = checkinventory(agent, input)
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function checkinventory(a::T1, input::T2
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)::Union{Tuple{String, Number, Number, Bool}, Tuple{String, Nothing, Number, Bool}} where {T1<:agent, T2<:AbstractString}
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wineattributes = extractWineAttributes(a, input)
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wineattributes_1 = extractWineAttributes_1(a, input)
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wineattributes_2 = extractWineAttributes_2(a, input)
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# replace because SQLLLM didn't know what food_paired means
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result = replace(wineattributes, "food_pairing" => "food_to_be_paired_with_wine")
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inventoryquery = "$wineattributes_1, $wineattributes_2"
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result = SQLLLM.query(result, a.executeSQL, a.text2textInstructLLM)
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result = SQLLLM.query(inventoryquery, a.executeSQL, a.text2textInstructLLM)
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return result
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end
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@@ -394,145 +394,51 @@ julia>
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# Signature
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"""
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function extractWineAttributes(a::T1, input::T2
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function extractWineAttributes_1(a::T1, input::T2
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)::String where {T1<:agent, T2<:AbstractString}
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converstiontable =
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"""
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Conversion Table:
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Intensity level:
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Level 1: May correspond to "light-bodied" or a similar description.
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Level 2: May correspond to "med light", "medium light" or a similar description.
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Level 3: May correspond to "medium" or a similar description.
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Level 4: May correspond to "med full", "medium full" or a similar description.
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Level 5: May correspond to "full" or a similar description.
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Sweetness level:
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Level 1: May correspond to "dry", "no sweet" or a similar description.
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Level 2: May correspond to "off dry", "less sweet" or a similar description.
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Level 3: May correspond to "semi sweet" or a similar description.
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Level 4: May correspond to "sweet" or a similar description.
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Level 5: May correspond to "very sweet" or a similar description.
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Tannin level:
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Level 1: May correspond to "low tannin" or a similar description.
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Level 2: May correspond to "semi low tannin" or a similar description.
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Level 3: May correspond to "medium tannin" or a similar description.
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Level 4: May correspond to "semi high tannin" or a similar description.
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Level 5: May correspond to "high tannin" or a similar description.
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Acidity level:
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Level 1: May correspond to "low acidity" or a similar description.
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Level 2: May correspond to "semi low acidity" or a similar description.
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Level 3: May correspond to "medium acidity" or a similar description.
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Level 4: May correspond to "semi high acidity" or a similar description.
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Level 5: May correspond to "high acidity" or a similar description.
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"""
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# systemmsg =
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# """
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# As an attentive sommelier, your task is to determine the user's wine preferred levels of sweetness, intensity, tannin, acidity and other criteria based on the user query.
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# At each round of conversation, the user will give you the current situation:
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# Conversion Table: ...
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# Query: ...
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# You must follow the following guidelines:
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# 1) If specific information is not available in the query, use "NA" to indicate this. Also words like "any" or "unlimited" means no information available.
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# 2) Use converstion table to convert sweetness, acidity, tannin, intensity describing word into an integer.
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# 3) Do not generate other comments.
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# You should then respond to the user with the following points:
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# - wine_type: Can be one of: red, white, sparkling, rose, dessert or fortified
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# - price: ...
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# - occasion: ...
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# - food_pairing: food that will be served with wine
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# - country: wine's country of origin
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# - grape_variety: ...
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# - tasting_notes: wine's flavors
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# - sweetness: S where S is an integer indicating sweetness level
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# - acidity: A where A is an integer indicating acidity level
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# - tannin: T where T is an integer indicating tannin level
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# - intensity: I where I is an integer indicating intensity level
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# You should only respond in format as described below:
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# repeat: repeat the user's query
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# wine_type: ...
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# price: ...
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# occasion: ...
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# food_pairing: ...
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# country: ...
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# grape_variety: ...
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# tasting_notes: ...
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# sweetness:
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# acidity: ...
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# tannin: ...
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# intensity: ...
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# Here are some examples:
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# user: "price < 25, for wedding party, full-bodied white wine with sweetness level 2, apple and honey notes, low tannin level and medium acidity level, Pizza, France, Riesling"
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# assistant: repeat: ... \n wine_type: white\n price: less than 25\n occasion: wedding party\n food_pairing: Pizza\n country: France\n grape_variety: Riesling\n tasting_notes: apple, honey\n sweetness: 2\n acidity: 3\n tannin: 1\n intensity: 5
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# user: body=full-bodied, dry, acidity=medium and low tannin
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# assistant: repeat: ... \n wine_type: NA\n price: NA\n occasion: NA\n food_pairing: NA\n country: NA\n grape_variety: NA\n tasting_notes: NA\n sweetness: 1\n acidity: 3\n tannin: 1\n intensity: 5
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# Let's begin!
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# """
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systemmsg =
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"""
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As an attentive sommelier, your task is to fillout the form based on the user query. The form is about the user's wine preference.
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As an helpful sommelier, your task is to fill the user's preference form based on the user query.
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At each round of conversation, the user will give you the current situation:
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Conversion Table: ...
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Query: ...
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User query: ...
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The preference form requires the following information:
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wine_type, price, occasion, food_to_be_paired_with_wine, country, grape_variety, wine_notes.
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You must follow the following guidelines:
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1) Use the conversion table to convert the descriptive word level of sweetness, intensity, tannin, and acidity into a corresponding integer.
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2) If specific information required in the form is not available in the query, use 'NA' to indicate this. Additionally, words like 'any' or 'unlimited' mean no information is available.
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1) If specific information required in the preference form is not available in the query, use 'NA' to indicate this.
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Additionally, words like 'any' or 'unlimited' mean no information is available.
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2) Use the conversion table to convert the descriptive word level of sweetness, intensity, tannin, and acidity into a corresponding integer.
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3) Do not generate other comments.
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You should then respond to the user with the following points:
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1) reasoning: State your reasoning about the current situation.
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2) wine_type: Can be one of: red, white, sparkling, rose, dessert or fortified
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3) price: ...
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4) occasion: ...
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5) food_to_be_paired_with_wine: food that will be served with wine
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6) country: wine's country of origin
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7) grape_variety: ...
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8) tasting_notes: wine's flavors
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9) sweetness: S where S is an integer indicating sweetness level
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10) acidity: A where A is an integer indicating acidity level
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11) tannin: T where T is an integer indicating tannin level
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12) intensity: I where I is an integer indicating intensity level
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- wine_type: Can be one of: red, white, sparkling, rose, dessert or fortified
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- price: ...
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- occasion: ...
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- food_to_be_paired_with_wine: food that will be served with wine
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- country: wine's country of origin
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- grape_variety: ...
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- wine_notes:
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Bad example (these words are not wine notes - descriptive words): dry, sour, full bodied, etc.
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Good example (these words are wine notes - descriptive words): floral, citrus, earthy, fruity, tropical, nutty, etc.
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You should only respond in format as described below:
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reasoning: ...
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You should only respond in the form as described below:
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wine_type: ...
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price: ...
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occasion: ...
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food_to_be_paired_with_wine: ...
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country: ...
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grape_variety: ...
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tasting_notes: ...
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sweetness:
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acidity: ...
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tannin: ...
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intensity: ...
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Here are some examples:
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user: price < 25, for wedding party, full-bodied white wine with sweetness level 2, apple and honey notes, low tannin level and medium acidity level, Pizza, France, Riesling
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assistant: reasoning: ... \n wine_type: white\n price: less than 25\n occasion: wedding party\n food_to_be_paired_with_wine: Pizza\n country: France\n grape_variety: Riesling\n tasting_notes: apple, honey\n sweetness: 2\n acidity: 3\n tannin: 1\n intensity: 5
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user: body=full-bodied, dry, acidity=medium and low tannin
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assistant: reasoning: ... \n wine_type: NA\n price: NA\n occasion: NA\n food_to_be_paired_with_wine: NA\n country: NA\n grape_variety: NA\n tasting_notes: NA\n sweetness: 1\n acidity: 3\n tannin: 1\n intensity: 5
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wine_notes: ...
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Let's begin!
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"""
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usermsg =
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"""
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Conversion Table: $converstiontable
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Query: $input
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User query: $input
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"""
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_prompt =
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@@ -548,7 +454,7 @@ function extractWineAttributes(a::T1, input::T2
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<|start_header_id|>assistant<|end_header_id|>
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"""
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attributes = ["reasoning", "wine_type", "price", "occasion", "food_to_be_paired_with_wine", "country", "grape_variety", "sweetness", "acidity", "tannin", "intensity"]
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attributes = ["wine_type", "price", "occasion", "food_to_be_paired_with_wine", "country", "grape_variety"]
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for attempt in 1:5
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try
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@@ -561,17 +467,9 @@ function extractWineAttributes(a::T1, input::T2
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end
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end
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# check if there are more than 1 key per categories
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for i ∈ attributes
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matchkeys = GeneralUtils.findMatchingDictKey(responsedict, i)
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if length(matchkeys) > 1
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error("generatechat has more than one key per categories")
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end
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end
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result = ""
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for (k, v) in responsedict
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if k != :reasoning && !occursin("NA", v)
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if !occursin("NA", v)
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result *= "$k: $v, "
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end
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end
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@@ -592,6 +490,215 @@ function extractWineAttributes(a::T1, input::T2
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error("wineattributes_wordToNumber() failed to get a response")
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end
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function extractWineAttributes_2(a::T1, input::T2
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)::String where {T1<:agent, T2<:AbstractString}
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converstiontable =
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"""
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Conversion Table:
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Intensity level:
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1: May correspond to "light-bodied" or a similar description.
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2: May correspond to "med light", "medium light" or a similar description.
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3: May correspond to "medium" or a similar description.
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4: May correspond to "med full", "medium full" or a similar description.
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5: May correspond to "full" or a similar description.
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Sweetness level:
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1: May correspond to "dry", "no sweet" or a similar description.
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2: May correspond to "off dry", "less sweet" or a similar description.
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3: May correspond to "semi sweet" or a similar description.
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4: May correspond to "sweet" or a similar description.
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5: May correspond to "very sweet" or a similar description.
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Tannin level:
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1: May correspond to "low tannin" or a similar description.
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2: May correspond to "semi low tannin" or a similar description.
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3: May correspond to "medium tannin" or a similar description.
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4: May correspond to "semi high tannin" or a similar description.
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5: May correspond to "high tannin" or a similar description.
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Acidity level:
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1: May correspond to "low acidity" or a similar description.
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2: May correspond to "semi low acidity" or a similar description.
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3: May correspond to "medium acidity" or a similar description.
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4: May correspond to "semi high acidity" or a similar description.
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5: May correspond to "high acidity" or a similar description.
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"""
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systemmsg =
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"""
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As an helpful sommelier, your task is to fill the user's preference form based on the user query.
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At each round of conversation, the user will give you the current situation:
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Conversion Table: ...
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User query: ...
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The preference form requires the following information:
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sweetness, acidity, tannin, intensity
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You must follow the following guidelines:
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1) If specific information required in the preference form is not available in the query, use 'NA' to indicate this.
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Additionally, words like 'any' or 'unlimited' mean no information is available.
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2) Use the conversion table to convert the descriptive word level of sweetness, intensity, tannin, and acidity into a corresponding integer.
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3) Do not generate other comments.
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You should then respond to the user with the following points:
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- sweetness: S where S is an integer indicating sweetness level
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- acidity: D where D is an integer indicating acidity level
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- tannin: T where T is an integer indicating tannin level
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- intensity: I where I is an integer indicating intensity level
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You should only respond in the form as described below:
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sweetness: ...
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acidity: ...
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tannin: ...
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intensity: ...
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Let's begin!
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"""
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usermsg =
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"""
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Conversion Table: $converstiontable
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User query: $input
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"""
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_prompt =
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[
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Dict(:name=> "system", :text=> systemmsg),
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Dict(:name=> "user", :text=> usermsg)
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]
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# put in model format
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prompt = GeneralUtils.formatLLMtext(_prompt, "llama3instruct")
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prompt *=
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"""
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<|start_header_id|>assistant<|end_header_id|>
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"""
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attributes = ["sweetness", "acidity", "tannin", "intensity"]
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for attempt in 1:5
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try
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response = a.text2textInstructLLM(prompt)
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responsedict = GeneralUtils.textToDict(response, attributes, rightmarker=":", symbolkey=true)
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for i ∈ attributes
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if length(JSON3.write(responsedict[Symbol(i)])) == 0
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error("$i is empty ", @__LINE__)
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end
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end
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result = ""
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for (k, v) in responsedict
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if !occursin("NA", v)
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result *= "$k: $v, "
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end
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end
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result = result[1:end-2] # remove the ending ", "
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return result
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catch e
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io = IOBuffer()
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showerror(io, e)
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errorMsg = String(take!(io))
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st = sprint((io, v) -> show(io, "text/plain", v), stacktrace(catch_backtrace()))
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println("")
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println("Attempt $attempt. Error occurred: $errorMsg\n$st")
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println("")
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end
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end
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error("wineattributes_wordToNumber() failed to get a response")
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end
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# function recheckWineAttributes(a::T1, input::T2
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# )::String where {T1<:agent, T2<:AbstractString}
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# systemmsg =
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# """
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# As an helpful sommelier, your task is to check what preferences the user mentioned in the query.
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# At each round of conversation, the user will give you the current situation:
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# User query: ...
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# The preferences are:
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# - wine type: red, white, sparkling, rose, dessert, fortified
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# - price
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# - occasion
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# - food to be paired with wine
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# - country
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# - grape_variety
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# - tasting_notes
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# - sweetness
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# - acidity
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# - tannin
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# - intensity: wine body e.g. full bodied, light bodied
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# You should then respond to the user with the following points:
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# 1) mentioned_preferences: list all the preferences in the user's query.
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# Good example: mentioned_preferences: "price", "country", "wine type"
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# You should only respond in the form as described below:
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# mentioned_preferences: ...
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# Let's begin!
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# """
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# usermsg =
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# """
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# User query: $input
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# """
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# _prompt =
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# [
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# Dict(:name=> "system", :text=> systemmsg),
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# Dict(:name=> "user", :text=> usermsg)
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# ]
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# # put in model format
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# prompt = GeneralUtils.formatLLMtext(_prompt, "llama3instruct")
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# prompt *=
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# """
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# <|start_header_id|>assistant<|end_header_id|>
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# """
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# attributes = ["mentioned_preferences"]
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# for attempt in 1:5
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# try
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# response = a.text2textInstructLLM(prompt)
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# responsedict = GeneralUtils.textToDict(response, attributes, rightmarker=":", symbolkey=true)
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# for i ∈ attributes
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# if length(JSON3.write(responsedict[Symbol(i)])) == 0
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# error("$i is empty ", @__LINE__)
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# end
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# end
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# result = ""
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# for (k, v) in responsedict
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# if !occursin("NA", v)
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# result *= "$k: $v, "
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# end
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# end
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# result = result[1:end-2] # remove the ending ", "
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# return result
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# catch e
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# io = IOBuffer()
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# showerror(io, e)
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# errorMsg = String(take!(io))
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# st = sprint((io, v) -> show(io, "text/plain", v), stacktrace(catch_backtrace()))
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# println("")
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# println("Attempt $attempt. Error occurred: $errorMsg\n$st")
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# println("")
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# end
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# end
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# error("wineattributes_wordToNumber() failed to get a response")
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# end
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""" Attemp to correct LLM response's incorrect JSON response.
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# Arguments
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Reference in New Issue
Block a user